library(tidyverse)
library(plotly)
getStarts <- function(d){
s = d %>% select(Stage, Nodes, Time, y) %>%
group_by(Stage, Nodes) %>%
summarise(Start=min(Time), y=min(y)) %>% arrange(Start)
return(s)
}
RESEARCH_HOME = "/home/and/Documents/PhD/Research"
lines = readLines(paste0(RESEARCH_HOME, "/Scripts/R/Benchmarks/MultiAndSingleNode/R12/aws/monitor.txt"))
lines = lines[grepl("\\|SCALE\\|", lines)]
monitor = as_tibble(lines) %>%
separate(value, into=c("Timestamp", "Scale", "Time", "ID", "Nodes", "Stage", "RDDs", "Task", "Dura", "Load"), sep="\\|") %>%
separate(ID, into=c(NA, NA, "ID"), sep="_") %>%
select(ID, Time, Nodes, Stage, RDDs, Task, Load) %>%
mutate(Time=as.numeric(Time), RDDs=as.numeric(RDDs), Tasks=as.numeric(Task), Load=as.numeric(Load)) %>%
group_by(ID, Time, Nodes, Stage) %>% summarise(RDDs=mean(RDDs), Tasks=mean(Tasks), Load=mean(Load))
head(monitor)
apps = monitor %>% ungroup() %>% select(ID, Nodes) %>% distinct()
head(apps, n=Inf)
d = monitor %>% filter(ID %in% c("0028","0029","0030")) %>% ungroup %>%
mutate(y = Load) %>%
select(Time, y, Nodes, Stage) %>%
arrange(Time)
head(d, n=30)
p = ggplot(data = d, aes(x = Time, y = y, group = 1, color = Nodes, linetype = Nodes)) +
geom_line() +
geom_point(data = getStarts(d), aes(x=Start, y=y, group=1, color=Nodes, text = paste(Stage,"<br>Start:",Start,"<br>",y)))
Ignoring unknown aesthetics: text
ggplotly(p, tooltip = c("text"))
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